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Stocks making the biggest moves premarket: Lam Research, Intel, DataDog & more

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Artificial IntelligenceTechnology & InnovationAnalyst EstimatesCompany FundamentalsAnalyst Insights
Stocks making the biggest moves premarket: Lam Research, Intel, DataDog & more

Semiconductor sentiment improved materially: SOXX rebounded more than 2.5% premarket after a prior two-day slide of over 11%, with Intel up ~2.5% and AMD up ~3%. ASML rose ~4% after Bernstein lifted its price target by >30% to $2,300, citing AI-driven expansion in logic and DRAM capacity, while Morgan Stanley raised targets across Lam Research (+4%+), Applied Materials (~4%), and KLA (~4%). Offsetting some risk, DataDog fell >2% after Bernstein downgraded it to market-perform, and Comcast added ~0.5% on Sky’s plan to buy ITV’s TV business.

Analysis

This looks less like a broad “AI wins” re-rating and more like the market paying up for the layer that actually monetizes incremental capex: equipment, metrology, and process control. ASML is the cleanest structural winner because it sits closest to the bottleneck; if logic and DRAM expansion is real, its revenue inflects with a lag but carries unusually durable pricing power and service mix. LRCX/AMAT/KLAC should also capture a disproportionate share of any budget step-up, and their second-order benefit is better aftermarket revenue if installed-base utilization stays high. The key near-term issue is whether this is a squeeze off last week’s air pocket or the start of a higher earnings path. If hyperscaler AI spend merely rotates rather than broadens, the beta names can fade quickly, while the tool names hold up better because capex dollars flow before unit demand shows up in chips. The falsifier is any evidence that foundry, DRAM, or logic budgets are being deferred; if that happens, the current rebound can retrace in days, not months. DDOG is the more fragile setup: the market is still willing to own an AI story, but it now has to prove that AI contribution offsets slower core growth and harder comps. That creates a flatter risk/reward into earnings, with multiple compression possible even on “good enough” numbers. TMUS is a separate defensive beneficiary, but it reads more like a crowded quality/rate trade than a catalyst-rich AI expression.